A computer-implemented method, related system, and computer program product are provided for controlling an agricultural tool towed by a pivotally attached vehicle. A computer stores a model of the position and heading of the tool and the vehicle. The computer determines a velocity and turn rate of the vehicle based on position data from a first GPS receiver attached to the vehicle. The computer calculates the modeled position of the vehicle and the tool at a future time based on the velocity and turn rate of the vehicle. The computer also corrects the modeled position and heading of the vehicle and tool, based on position data from the first GPS receiver, and from a second GPS receiver attached to the tool, respectively. The computer generates a control signal to control an actuator associated with the tool based on the modeled position of the tool at the future time.

Implementations are described herein for analyzing vision data depicting undesirable plants such as weeds to detect various attribute(s). The detected attribute(s) of a particular undesirable plant may then be used to select, from a plurality of available candidate remediation techniques, the most suitable remediation technique to eradicate or otherwise eliminate the undesirable plants.

Embodiments of the present disclosure relate generally to generating and utilizing three-dimensional terrain maps for vehicular control. Other embodiments may be described and/or claimed.

The present invention provides an autonomous traveling work machine that can accurately receive positioning signals from navigation satellites and autonomously travel without deviating from a traveling path, even in the case of an inclined slope. The autonomous traveling work machine includes a traveling machine body, a positioning receiver that receives positioning signals from navigation satellites, an autonomous traveling control device that performs control for autonomous traveling along traveling paths based on the positioning signals, an inclination detection unit that detects the inclination of the traveling machine body and outputs inclination angle information, an inclination angle determination unit that determines an inclination angle based on the inclination angle information, and a rotation control mechanism that rotates the positioning receiver with one or more degrees of freedom. The rotation control mechanism keeps the positioning receiver horizontal based on the inclination angle.

Systems and methods for agricultural path planning are described. For example, a method includes accessing a boundary data structure that encodes a polygon on a map; generating a set of parallel line segments of a path for a vehicle on the map inside of the polygon; generating a first line segment of the path connecting an ending-point of one of the line segments of the set to a starting-point of another one of the line segments of the set; identifying a first point on the first line segment that is a maximum distance from the polygon; and splitting the first line segment into two line segments, having a starting-point matching a starting-point of the first line segment and an ending-point matching an ending-point of the first line segment, that connect at a second point on the polygon encoded by the boundary data structure that is closest to the first point.

Disclosed here are methods and systems for automatically operating automated vehicles moving through vegetation obstacles with minimal damage, comprising receiving image(s) depicting vegetation obstacle(s) blocking at least partially a path of an automated vehicle executing a mission, analyzing the image(s) to extract one or more obstacle attributes of the vegetation obstacle(s), computing a plurality of movement patterns for operating the automated to cross the vegetation obstacle(s) based on one or more vehicle attributes of the automated vehicle with respect to one or more of the obstacle attributes where each movement pattern defines one or more movement parameters of the automated vehicle, selecting one of the movement patterns estimated to reduce a cost of damage to the automated vehicle and/or to the one or more vegetation obstacles, and outputting instructions for operating the automated vehicle to move through the vegetation obstacle(s) according to the selected movement pattern.

Control zones are identified on a thematic map and work machine actuator settings are identified for each control zone. A position of the work machine is sensed and actuators on the work machine are controlled based on the control zone that the work machine is in, and based upon the actuator settings corresponding to the control zone. The control zone is then divided, on a display, into a harvested portion of the control zone on which an observed condition value is shown, and control zone that has yet to be harvested, on which an estimated value of the condition is shown.

Sensor systems for communications between heavy equipment machines during tree felling operations. A system includes a first heavy equipment comprising a first winch and a second heavy equipment comprising a second winch. The system includes a first cable attached to the first winch and a fulcrum roller and a second cable attached to the second winch and the fulcrum roller. The system is such that the first heavy equipment communicates with the second heavy equipment by way of long-range radio signals.

An autonomous farming machine navigable in an environment for performing farming action(s) is disclosed. The farming machine receives a notification from a manager that there are no obstacles in the blind spots of the detection system. The farming machine applies an obstacle detection model to the captured images to verify that there are no obstacles in unobstructed views. The farming machine determines a configuration of the farming machine. The farming machine determines a virtual safety bubble for the farming machine to autonomously perform the farming action(s) based on the determined configuration. The farming machine detects an obstacle in the environment by applying the obstacle detection model to the captured images. The farming machine determines that the obstacle is entering the virtual safety bubble. In response to determining that the obstacle is entering the virtual safety bubble, the farming machine terminates operation of the farming machine and/or enacts preventive measures.

A method of controlling a work machine on a worksite includes receiving an indication of a work machine assignment having a worksite location and corresponding assignment criteria associated with completion of the work machine assignment, receiving a set of worksite conditions at the location, and identifying a set of machine capabilities, each machine capability corresponding to operation of a controllable subsystem on the work machine. The method includes generating a likelihood metric indicative of a likelihood that the assignment criteria will be met based on the set of worksite conditions and the set of machine capabilities, comparing the likelihood metric to a threshold, and generating a control signal that controls the work machine based on the comparison.